December 2023 arXiv papers — page 30

Simon Martin Breum, Daniel Vædele Egdal, Victor Gram Mortensen, Anders Giovanni Møller

The increasing capability of Large Language Models to act as human-like social agents raises two important questions in the area of opinion dynamics. First, whether these agents can generate effective arguments that could be injected into the online discourse to steer the public opinion. Second, whether artificial agents can interact with each other to repro

Akram Abderraouf Gharbi, Ammar Chouchane, Abdelmalik Ouamane

Person re-identification (PRe-ID) is a computer vision issue, that has been a fertile research area in the last few years. It aims to identify persons across different non-overlapping camera views. In this paper, We propose a novel PRe-ID system that combines tensor feature representation and multilinear subspace learning. Our method exploits the power of pr

Sergei Adler, Hermann Boos

We consider the XXZ spin chain in the scaling limit in the Matsubara direction. The main result of this paper is new representations for the functions $\Psi(l, \kappa)$ and $\Theta(l, m; \kappa, \alpha)$ associated with the function $\omega(\zeta, \xi; \kappa, \kappa)$ found in the expression for the correlation function of the generators of the fermionic ba

Juan P. Oriana, German A. Patterson, Daniel R. Parisi

This study introduces a unique active matter system as an application of the pedestrian collision avoidance paradigm, that proposes dynamically adjusting the desired velocity. We present a fictitious human-zombie scenario set within a closed geometry, combining prey-predator behavior with a one-way contagion process that can transform prey into predators. Th

Riccardo Zuliani, Efe C. Balta, John Lygeros

Model predictive control (MPC) is pervasive in research and industry. However, designing the cost function and the constraints of the MPC to maximize closed-loop performance remains an open problem. To achieve optimal tuning, we propose a backpropagation scheme that solves a policy optimization problem with nonlinear system dynamics and MPC policies. We enfo

Charles Dickens, Eddie Huang, Aishwarya Reganti, Jiong Zhu

Graph summarization as a preprocessing step is an effective and complementary technique for scalable graph neural network (GNN) training. In this work, we propose the Coarsening Via Convolution Matching (CONVMATCH) algorithm and a highly scalable variant, A-CONVMATCH, for creating summarized graphs that preserve the output of graph convolution. We evaluate C

Hélène Langlois, Frédéric Meunier, Romeo Rizzi, Stéphane Vialette

In a digraph, a quasi-kernel is a subset of vertices that is independent and such that the shortest path from every vertex to this subset is of length at most two. The ``small quasi-kernel conjecture,'' proposed by Erd\H{o}s and Sz\'ekely in 1976, postulates that every sink-free digraph has a quasi-kernel whose size is within a fraction of the total number o

Jin-Wen Kang, Sa Wang, Lei Wang, Ben-Wei Zhang

This paper presents a phenomenological study on the angle between the Standard and the Winner-Take-All (WTA) jet axes ($\Delta R_{{\rm axis}}^{{\rm WTA-Std}}$) in high-energy nuclear collisions. The $p$+$p$ baseline is provided by the Pythia8 event generator. The in-medium jet propagation is simulated by the linear Boltzmann transport (LBT) model, which cons

Adam M Tahir

In this paper, it is shown that every polynomial function is mixed monotone globally with a polynomial decomposition function. For univariate polynomials, the decomposition functions can be constructed from the Gram matrix representation of polynomial functions. The tightness of polynomial decomposition functions is discussed. Several examples are provided.

Jinchao Zhu, Yuxuan Wang, Xiaobing Tu, Siyuan Pan

The Stable Diffusion Model (SDM) is a popular and efficient text-to-image (t2i) generation and image-to-image (i2i) generation model. Although there have been some attempts to reduce sampling steps, model distillation, and network quantization, these previous methods generally retain the original network architecture. Billion scale parameters and high comput

Kaveh Delfanazari

High-temperature superconductor (HTS) BSCCO-based coherent terahertz (THz) sources have shown great potential as one of the leading solid-state platforms in THz science and technology. Stable, and chip-scale photonic components must be developed to effectively and efficiently control and manipulate their coherent radiation, especially for future communicatio

Dasol Choi, Dongbin Na

Recent remarkable success in the deep-learning industries has unprecedentedly increased the need for reliable model deployment. For example, the model should alert the user if the produced model outputs might not be reliable. Previous studies have proposed various methods to solve the Out-of-Distribution (OOD) detection problem, however, they generally requi

Bruce C. Berndt, Örs Rebák

On page 206 in his lost notebook, Ramanujan recorded an incomplete septic theta function identity. Motivated by the completion of this identity by the second author, we offer cubic and quintic analogues. Using the theory generated by these two analogues and Ramanujan's class invariants, we provide many evaluations for Ramanujan's most prominent theta functio

Lucas Javier Albornoz, Rebeca Díaz Pardo, Aristide Lemaître, Sebastian Bustingorry

We explore the contributions of adiabatic and non-adiabatic spin-transfer torques (STT) of a spin-polarized current to the thermally activated creep motion of domain-walls in a thin (Ga,Mn)(As,P) film with perpendicular anisotropy. For a domain-wall transverse to current, the non-adiabatic STT is found to act as an external magnetic field. Close to the compe

Ismael Bailleul, Nguyen Viet Dang, Léonard Ferdinand, Gaëtan Leclerc

We argue that the spectrally cut-off Gaussian free field $\Phi_\Lambda$ on a compact Riemannian manifold or on $\mathbb{R}^n$ cannot satisfy the spatial Markov property. Moreover, when the manifold is reflection positive, we show that $\Phi_\Lambda$ fails to be reflection positive. We explain the difficulties one encounters when trying to deduce the reflecti

Dhruv Arora, Muhammad Yasir, Himanshu Chaudhary, Faisal Javed

This study examines a recently hypothesized black hole. We study the Joule-Thomson coefficient, the inversion temperature and also the isenthalpic curves in the $T_i -P_i$ plane. A comparison is made between the Van der Waals fluid and the black hole to study their similarities and differences. The Joule-Thomson coefficient, the inversion curves and the isen

Chuqi Cao, Dingqun Deng, Xingyu Li

In this paper, we study the Vlasov-Maxwell-Boltzmann system without angular cutoff and the Vlasov-Maxwell-Landau/Boltzmann system with polynomial perturbation $F=\mu+f$ near global Maxwellian. In particular, we prove the global existence, uniqueness and large time behavior for solutions in a polynomial weighted space $H^N_{x,v}(\langle v\rangle^k)$. The meth

Adam Doliwa

We study multiple orthogonal polynomials exploiting their explicit determinantal representation in terms of moments. Our reasoning follows that applied to solve the Hermite-Pad\'{e} approximation and interpolation problems. We study also families of multiple orthogonal polynomials obtained by variation of the measures known from the theory of discrete-time T

Chandrashekar Iyer, Mustansir Barma, Hunnervir Singh, Deepak Dhar

As the simplest model of transport of interacting particles in a disordered medium, we consider the asymmetric simple exclusion process (ASEP) in which particles with hard-core interactions perform biased random walks, on the supercritical percolation cluster. In this process, the long time trajectory of a marked particle consists of steps on the backbone, p

Sijie Ji, Xuanye Zhang, Yuanqing Zheng, Mo Li

This paper presents HandFi, which constructs hand skeletons with practical WiFi devices. Unlike previous WiFi hand sensing systems that primarily employ predefined gestures for pattern matching, by constructing the hand skeleton, HandFi can enable a variety of downstream WiFi-based hand sensing applications in gaming, healthcare, and smart homes. Deriving th

Hao Zhang, Shuangyou Zhang, Toby Bi, George Ghalanos

We demonstrate Kerr soliton frequency comb generation that is seeded by a cascaded Brillouin scattering process. In this process, a pump laser is used to generate multiple orders of Brillouin sidebands in a microresonator, which in turn generate the soliton. In such a process, even orders of Brillouin scattering sidebands are co-propagating with respect to t

Asier Alonso-Bardaji, David Brizuela

We provide a covariant framework to study singularity-free Lema\^itre-Tolman-Bondi spacetimes with effective corrections motivated by loop quantum gravity. We show that, as in general relativity, physically reasonable energy distributions lead to a contraction of the dust shells. However, quantum-gravity effects eventually stop the collapse, the dust smoothl

Rongen Dong, Feng Shu, Fuhui Zhou, Yongpeng Wu

With the aim of boosting the security of the conventional directional modulation (DM) network, a secure DM network assisted by intelligent reflecting surface (IRS) is investigated in this paper. To maximize the secrecy rate (SR), we jointly optimize the power allocation (PA) factor, confidential message (CM) beamforming, artificial noise (AN) beamforming, an

Zheng Liu, Chaofan Li, Shitao Xiao, Yingxia Shao

Dense retrieval calls for discriminative embeddings to represent the semantic relationship between query and document. It may benefit from the using of large language models (LLMs), given LLMs' strong capability on semantic understanding. However, the LLMs are learned by auto-regression, whose working mechanism is completely different from representing whole

Sahar Arshad, Seemab Latif, Ahmad Salman, Rabia Latif

Financial forecasting plays an important role in making informed decisions for financial stakeholders, specifically in the stock exchange market. In a traditional setting, investors commonly rely on the equity research department for valuable reports on market insights and investment recommendations. The equity research department, however, faces challenges

Wan Wang, Haiyan Wang, Adam J. Sobey

Problem definition: Supply chains are constantly evolving networks. Reinforcement learning is increasingly proposed as a solution to provide optimal control of these networks. Academic/practical: However, learning in continuously varying environments remains a challenge in the reinforcement learning literature.Methodology: This paper therefore seeks to addre

Atul Dixit

In this expository article, we discuss the contributions made by several mathematicians with regard to a famous formula of Ramanujan for odd zeta values. The goal is to complement the excellent survey by Berndt and Straub \cite{berndtstraubzeta} with some of the recent developments that have taken place in the area in the last decade or so.

Huadan Xu, Tianyou Wang, Zhizhao Che

Hypothesis: Droplet coalescence process is important in many applications and has been studied extensively when two droplets are surrounded by gas. However, the coalescence dynamics would be different when the two droplets are surrounded by an external viscous liquid. The coalescence of immiscible droplets in liquids has not been explored. Experiments: In th

Yuanyuan Zhang, Aaricia Herygers, Tanvina Patel, Zhengjun Yue

Automatic speech recognition (ASR) should serve every speaker, not only the majority ``standard'' speakers of a language. In order to build inclusive ASR, mitigating the bias against speaker groups who speak in a ``non-standard'' or ``diverse'' way is crucial. We aim to mitigate the bias against non-native-accented Flemish in a Flemish ASR system. Since this

Zhikun Xu, Yue Zhang, Tianyou Wang, Zhizhao Che

Hypothesis: Immiscible liquids are commonly used to achieve unique functions in many applications, where the breakup of compound droplets in airflow is an important process. Due to the existence of the liquid-liquid interface, compound droplets are expected to form different deformation and breakup morphologies compared with single-component droplets. Experi

Corneliu Arsene, Alessandra Parisio

Forecasting power consumptions of integrated electrical, heat or gas network systems is essential in order to operate more efficiently the whole energy network. Multi-energy systems are increasingly seen as a key component of future energy systems, and a valuable source of flexibility, which can significantly contribute to a cleaner and more sustainable whol

Christoph Dalitz, Juliane Arning, Steffen Goebbels

Chatterjee's rank correlation coefficient $\xi_n$ is an empirical index for detecting functional dependencies between two variables $X$ and $Y$. It is an estimator for a theoretical quantity $\xi$ that is zero for independence and one if $Y$ is a measurable function of $X$. Based on an equivalent characterization of sorted numbers, we derive an upper bound f

Amaia Razquin, MyeongJae Lee

An implementation of A Common Tracking Software (ACTS) toolkit for signal electron reconstruction for the COMET muon to electron conversion experiment is discussed. The COMET experiment in J-PARC, Japan, will search for neutrinoless conversion of muons into electrons in the field of an aluminium nucleus, a lepton flavour violating process, aiming target sens

Alexander Chudik, M. Hashem Pesaran, Mahrad Sharifvaghefi

This paper considers the problem of variable selection allowing for parameter instability. It distinguishes between signal and pseudo-signal variables that are correlated with the target variable, and noise variables that are not, and investigate the asymptotic properties of the One Covariate at a Time Multiple Testing (OCMT) method proposed by Chudik et al.

Remy L. Delva, Jonas Mielke, Guido Burkard, Jason R. Petta

Measurement-based entanglement is a method for entangling quantum systems through the state projection that accompanies a parity measurement. We derive a stochastic master equation describing measurement-based entanglement of a pair of silicon double-dot flopping-mode spin qubits, develop numerical simulations to model this process, and explore what modifica

Duo Zhang, Xinzijian Liu, Xiangyu Zhang, Chengqian Zhang

The rapid advancements in artificial intelligence (AI) are catalyzing transformative changes in atomic modeling, simulation, and design. AI-driven potential energy models have demonstrated the capability to conduct large-scale, long-duration simulations with the accuracy of ab initio electronic structure methods. However, the model generation process remains

Huadan Xu, Tianyou Wang, Zhizhao Che

Hypothesis: Droplet coalescence is a common phenomenon and plays an important role in many applications. When two liquid droplets are brought into contact, a liquid bridge forms and expands quickly. Different from miscible droplets, an extra immiscible interface exists throughout the coalescence of immiscible droplets and is expected to affect the evolution

Ling Li, Shaohua Li, June Tay, Huijing Zhan

Denoising Diffusion Probabilistic Model (DDPM) has shown great competence in image and audio generation tasks. However, there exist few attempts to employ DDPM in the text generation, especially review generation under recommendation systems. Fueled by the predicted reviews explainability that justifies recommendations could assist users better understand th

Marcos Oliveira, Junran Yang, Daniel Griffiths, Denis Bonnay

How easy is it to uniquely identify a person based solely on their web browsing behavior? Here we show that when people navigate the Web, their online traces produce fingerprints that identify them. Merely the four most visited web domains are enough to identify 95% of the individuals. These digital fingerprints are stable and render high re-identifiability.

Anurag Dutta, K. Lakshmanan, John Harshith, A. Ramamoorthy

Time Complexity is an important metric to compare algorithms based on their cardinality. The commonly used, trivial notations to qualify the same are the Big-Oh, Big-Omega, Big-Theta, Small-Oh, and Small-Omega Notations. All of them, consider time a part of the real entity, i.e., Time coincides with the horizontal axis in the argand plane. But what if the Ti

Marcos V. Conde, Florin Vasluianu, Radu Timofte

In smartphones and compact cameras, the Image Signal Processor (ISP) transforms the RAW sensor image into a human-readable sRGB image. Most popular super-resolution methods depart from a sRGB image and upscale it further, improving its quality. However, modeling the degradations in the sRGB domain is complicated because of the non-linear ISP transformations.

G. Mustafa

The current study deals with the new wormhole solutions in the background of fourth order new modified Ricci inverse gravity. Two new classes of the wormhole solutions are analyzed by showing the valid region for the main part of wormhole geometry under the affect of involved parameters. The embedded diagrams for both generic shape functions are also present

A. Romero Francia, A. Perillo Marcone, S. Pianese, K. Andersen

The Super Proton Synchrotron (SPS) is the last stage in the injector chain for CERN's Large Hadron Collider, and it also provides proton and ion beams for several fixed-target experiments. The SPS has been in operation since 1976, and it has been upgraded over the years. For the SPS to operate safely, its internal beam dump must be able to repeatedly absorb

Bin Shen, Dingli Xia

In this manuscript, we study the positive solutions of the Finslerian Fisher-KPP equation $$ u_t=\Delta^{\nabla u} u+cu(1-u). $$ The Fisher-KPP equation is widely applied and connected to many mathematical branches. We establish the global gradient estimates on compact Finsler metric measure manifold with the traditional $CD(K,N)$ condition, which is develop

Qu Cao, Song He, Yichao Tang

We prove that all tree-level $n$-point supergluon (scalar) amplitudes in AdS$_5$ can be recursively constructed, using factorization and flat-space limit. Our method is greatly facilitated by a natural R-symmetry basis for planar color-ordered amplitudes, which reduces the latter to "partial amplitudes" with simpler pole structures and factorization properti

Maksim V. Kukushkin

In this paper we study spectral properties of non-selfadjoint operators with the discrete spectrum. The main challenge is to represent a complete description of belonging to the Schatten class through the properties of the Hermitian real component. The method of estimating the singular values is elaborated by virtue of the established asymptotic formulas. Th

Fotios K. Anagnostopoulos, Emanuel N. Saridakis

We confront massive Proca-Nuevo gravity with cosmological observations. The former is a non-linear theory involving a massive spin-1 field, that can be extended incorporating operators of the Generalized Proca class, and when coupled to gravity it can be covariantized in a way that exhibits consistent and ghost-free cosmological solutions, without experienci

Andrea Gambassi, S. Dietrich

We review recent advances in the theoretical, numerical, and experimental studies of critical Casimir forces in soft matter, with particular emphasis on their relevance for the structures of colloidal suspensions and on their dynamics. Distinct from other interactions which act in soft matter, such as electrostatic and van der Waals forces, critical Casimir

Rui Zhou, Haiyang Zhang, Hao Wang, Jin He

By integrating the local voltage-controlled magnetic anisotropy (VCMA) effect, Dzyaloshinskii-Moriya interaction (DMI) effect, and spin-orbit torque (SOT) effect, we propose a novel device structure for field-free magnetic tunnel junction (MTJ). Micromagnetic simulation shows that the device utilizes the chiral symmetry breaking caused by the DMI effect to i

Shufang Zhang, Minxue Ni, Lei Wang, Wenxin Ding

The Diffusion model has a strong ability to generate wild images. However, the model can just generate inaccurate images with the guidance of text, which makes it very challenging to directly apply the text-guided generative model for virtual try-on scenarios. Taking images as guiding conditions of the diffusion model, this paper proposes a brand new persona

Vishwa Prakash H. V., Prajakta Nimbhorkar

We study the fair allocation of indivisible goods and chores under ordinal valuations for agents with unequal entitlements. We show the existence and polynomial time computation of weighted necessarily proportional up to one item (WSD-PROP1) allocations for both goods and chores, by reducing it to a problem of finding perfect matchings in a bipartite graph.

Guanqun Bi, Yuqiang Xie, Lei Shen, Yanan Cao

The need to assess LLMs for bias and fairness is critical, with current evaluations often being narrow, missing a broad categorical view. In this paper, we propose evaluating the bias and fairness of LLMs from a group fairness lens using a novel hierarchical schema characterizing diverse social groups. Specifically, we construct a dataset, GFAIR, encapsulati

Moritz Bensberg, Markus Reiher

Exploring large chemical reaction networks with automated exploration approaches and accurate quantum chemical methods can require prohibitively large computational resources. Here, we present an automated exploration approach that focuses on the kinetically relevant part of the reaction network by interweaving (i) large-scale exploration of chemical reactio

Abhay Srivastav, Saronath Halder

We explore entanglement as a resource to distinguish locally indistinguishable orthogonal quantum states. Specifically, we consider sets which contain states from an unextendible product basis along with a pure entangled state. We establish a connection between the aforesaid problem and the entanglement-assisted discrimination of a certain class of many-copy

Antonio Mastropaolo, Matteo Ciniselli, Massimiliano Di Penta, Gabriele Bavota

Several code summarization techniques have been proposed in the literature to automatically document a code snippet or a function. Ideally, software developers should be involved in assessing the quality of the generated summaries. However, in most cases, researchers rely on automatic evaluation metrics such as BLEU, ROUGE, and METEOR. These metrics are all

Paul Daoudi, Christophe Prieur, Bogdan Robu, Merwan Barlier

Off-dynamics Reinforcement Learning (ODRL) seeks to transfer a policy from a source environment to a target environment characterized by distinct yet similar dynamics. In this context, traditional RL agents depend excessively on the dynamics of the source environment, resulting in the discovery of policies that excel in this environment but fail to provide r

Andrea Pinamonti, Giorgio Stefani, Simone Verzellesi

We prove that the boundary of an almost minimizer of the intrinsic perimeter in a plentiful group can be approximated by intrinsic Lipschitz graphs. Plentiful groups are Carnot groups of step~$2$ whose center of the Lie algebra is generated by any co-dimension one horizontal subspace. For example, $H$-type groups not isomorphic to the first Heisenberg group

Jasmin Mousavi, Arash Termehchy

Large language models have shown unprecedented abilities in generating linguistically coherent and syntactically correct natural language output. However, they often return incorrect and inconsistent answers to input questions. Due to the complexity and uninterpretability of the internally learned representations, it is challenging to modify language models

Rashik Shrestha, Ajad Chhatkuli, Menelaos Kanakis, Luc Van Gool

Local image feature descriptors have had a tremendous impact on the development and application of computer vision methods. It is therefore unsurprising that significant efforts are being made for learning-based image point descriptors. However, the advantage of learned methods over handcrafted methods in real applications is subtle and more nuanced than exp

Zhiwen Chen, Zhiyu Zhu, Yifan Zhang, Junhui Hou

In this paper, we delve into the nuanced challenge of tailoring the Segment Anything Models (SAMs) for integration with event data, with the overarching objective of attaining robust and universal object segmentation within the event-centric domain. One pivotal issue at the heart of this endeavor is the precise alignment and calibration of embeddings derived

Alexander Migdal

This paper presents a recent advancement that transforms the problem of decaying turbulence in the Navier-Stokes equations in $3+1$ dimensions into a Number Theory challenge: finding the statistical limit of the Euler ensemble. We redefine this ensemble as a Markov chain, establishing its equivalence to the quantum statistical theory of $N$ fermions on a rin

Gan Yuan, Mingyue Xu, Samory Kpotufe, Daniel Hsu

We consider the problem of sufficient dimension reduction (SDR) for multi-index models. The estimators of the central mean subspace in prior works either have slow (non-parametric) convergence rates, or rely on stringent distributional conditions (e.g., the covariate distribution $P_{\mathbf{X}}$ being elliptical symmetric). In this paper, we show that a fas

Claudio Bonanno, Francesco D'Angelo, Massimo D'Elia, Lorenzo Maio

We compute the sphaleron rate on the lattice. We adopt a novel strategy based on the extraction of the spectral density via a modified version of the Backus-Gilbert method from finite-lattice-spacing and finite-smoothing-radius Euclidean topological charge density correlators. The physical sphaleron rate is computed by performing controlled continuum limit a

Thore Gerlach, Stefan Knipp, David Biesner, Stelios Emmanouilidis

Field-Programmable Gate Arrays (FPGAs) have asserted themselves as vital assets in contemporary computing by offering adaptable, reconfigurable hardware platforms. FPGA-based accelerators incubate opportunities for breakthroughs in areas, such as real-time data processing, machine learning or cryptography -- to mention just a few. The procedure of placement

Tapan Kumar Das, Ron Naaman, Jonas Fransson

Chiral oligopeptide monolayers were adsorbed on a ferromagnetic surface and their magnetoresistance was measured as a function of the angle between the magnetization of the ferromagnet and the surface normal. These measurements were conducted as a function of temperature for both enantiomers. The angle dependence was found to follow the cosine square functio

Eric Ballouz, Scott T. M. Dawson, H. Jane Bae

In this work, we study the transient growth of the principal resolvent modes in the minimal flow unit using a reformulation of resolvent analysis in a time-localized wavelet basis. We target the most energetic spatial wavenumbers for the minimal flow unit and obtain modes that are constant in the streamwise direction and once-periodic in the spanwise directi

Boštjan Brešar, María Gracia Cornet, Tanja Dravec, Michael A. Henning

In this follow-up to [M.G.~Cornet, P.~Torres, arXiv:2308.15603], where the $k$-tuple domination number and the 2-packing number in Kneser graphs $K(n,r)$ were studied, we are concerned with two variations, the $k$-domination number, ${\gamma_{k}}(K(n,r))$, and the $k$-tuple total domination number, ${\gamma_{t\times k}}(K(n,r))$, of $K(n,r)$. For both invari

Yuanyuan Wang, Hangting Chen, Dongchao Yang, Jianwei Yu

The query-based audio separation usually employs specific queries to extract target sources from a mixture of audio signals. Currently, most query-based separation models need additional networks to obtain query embedding. In this way, separation model is optimized to be adapted to the distribution of query embedding. However, query embedding may exhibit mis

Mattia Romeo, Cesare Gagliardo, Grazia Cottone, Giorgio Collura

In the last years in-vivo tractography has assumed an important role in neurosciences, for both research and clinical applications such as non-invasive investigation of brain connectivity and presurgical planning in neurosurgery. In more recent years there has been a growing interest in the applications of diffusion tractography for target identification in

Wenshuai Liu

Recent simulations show that the eccentricity of supermassive binary black hole with intermediate mass ratio could grow toward near unity through gravitational interaction with the stellar background in the merging remnant after two galaxies merge. The increased eccentricity reduces the timescale of the supermassive binary black hole merger through the stron

Xiaojuan Liu, Maojun Li, Tao Yin

This paper studies a non-singular coupling scheme for solving the acoustic and elastic wave scattering problems and its extension to the problems of Laplace and Lam\'e equations and the problem with a compactly supported inhomogeneity is also briefly discussed. Relying on the solution representation of the wave scattering problem, a Robin-type artificial bou

Rohit Lal, Saketh Bachu, Yash Garg, Arindam Dutta

The capability to accurately estimate 3D human poses is crucial for diverse fields such as action recognition, gait recognition, and virtual/augmented reality. However, a persistent and significant challenge within this field is the accurate prediction of human poses under conditions of severe occlusion. Traditional image-based estimators struggle with heavy

Yuxiang Liang, Shun Zhang

In this paper, for the generalized Darcy problem (an elliptic equation with discontinuous coefficients), we study a special partial Least-Squares (Galerkin-least-squares) method, known as the augmented mixed finite element method, and its relationship to the standard least-squares finite element method (LSFEM). Two versions of augmented mixed finite element

Paul Daoudi, Mathias Formoso, Othman Gaizi, Achraf Azize

A precondition for the deployment of a Reinforcement Learning agent to a real-world system is to provide guarantees on the learning process. While a learning algorithm will eventually converge to a good policy, there are no guarantees on the performance of the exploratory policies. We study the problem of conservative exploration, where the learner must at l

Pierre-Alexandre Duverne, Stéphanie Hoang, Tito Dal Canton, Sarah Antier

Gravitational-wave data from interferometric detectors like LIGO, Virgo and KAGRA is routinely analyzed by rapid matched-filtering algorithms to detect compact binary merger events and rapidly infer their spatial position, which enables the discovery of associated non-GW transients like GRB 170817A and AT2017gfo. One of the critical requirements for finding

Dmitry Churikov

A group $G$ is said to be totally $k$-closed for a positive integer $k$ if, in each of its faithful permutation representations on a set $\Omega^k$, $G$ is the largest subgroup of the symmetric group $\operatorname{Sym}(\Omega)$ that preserves every $k$-orbit in the induced action on the set $\Omega\times\dots\times \Omega=\Omega^k$. We prove that for $k\geq

Sam Chow, Agamemnon Zafeiropoulos, Evgeniy Zorin

We introduce an inhomogeneous variant of Kaufman's measure, with applications to diophantine approximation. In particular, we make progress towards a problem related to Littlewood's conjecture.

Jie Cao, Xu Zhu, Sumei Sun, Ernest Kurniawan

Age of Information (AoI) has been proposed to quantify the freshness of information for emerging real-time applications such as remote monitoring and control in wireless networked control systems (WNCSs). Minimization of the average AoI and its outage probability can ensure timely and stable transmission. Energy efficiency (EE) also plays an important role i

Tosson Elalaily, Martin Berke, Ilari Lilja, Alexander Savin

The observation of the gate-controlled supercurrent (GCS) effect in superconducting nanostructures increased the hopes for realizing a superconducting equivalent of semiconductor field-effect transistors. However, recent works attribute this effect to various leakage-based scenarios, giving rise to a debate on its origin. A proper understanding of the micros

Qianchuan Wang, Junji Jia

The periapsis shift of charged test particles in arbitrary static and spherically symmetric charged spacetimes are studied. Two perturbative methods, the near-circular approximation and post-Newtonian methods, are developed, and shown to be very accurate when the results are found to high orders. The former method is more precise when the eccentricity $e$ of

Ivan Litvinov, Gal Spaer Milo, Alexander Liberzon, Slava Krylov

We report on the piezoresistive method for detecting stability loss events in microelectromechanical (MEMS) sensors based on bifurcation. The method involves measuring the resistivity changes of an entire beam to detect snap-through transitions in an electrostatically actuated, bistable double-clamped crystalline Silicon (Si) microbeam. The applicability of

Xiaopeng Li, Lixin Su, Pengyue Jia, Xiangyu Zhao

Search engines are crucial as they provide an efficient and easy way to access vast amounts of information on the internet for diverse information needs. User queries, even with a specific need, can differ significantly. Prior research has explored the resilience of ranking models against typical query variations like paraphrasing, misspellings, and order ch

Ming Yan, Ruihao Li, Hao Zhang, Hao Wang

Language agents have shown impressive problem-solving skills within defined settings and brief timelines. Yet, with the ever-evolving complexities of open-world simulations, there's a pressing need for agents that can flexibly adapt to complex environments and consistently maintain a long-term memory to ensure coherent actions. To bridge the gap between lang

Mirko Casu, Luca Guarnera, Pasquale Caponnetto, Sebastiano Battiato

This paper examines the impact of cognitive biases on decision-making in forensics and digital forensics, exploring biases such as confirmation bias, anchoring bias, and hindsight bias. It assesses existing methods to mitigate biases and improve decision-making, introducing the novel "Impostor Bias", which arises as a systematic tendency to question the auth

Dongmin Choi, Wonwoo Cho, Kangyeol Kim, Jaegul Choo

Accurately annotating multiple 3D objects in LiDAR scenes is laborious and challenging. While a few previous studies have attempted to leverage semi-automatic methods for cost-effective bounding box annotation, such methods have limitations in efficiently handling numerous multi-class objects. To effectively accelerate 3D annotation pipelines, we propose iDe

J. A. de la Torre, Pep Español

The phenomenon known as the tennis racket effect is observed when a rigid body experiences unstable rotation around its intermediate axis. In free space, this leads to the Dzhanibekov effect, where triaxial objects like a spinning wing bolt may continuously flip their rotational axis. Over time, however, dissipation ensures that a torque free spinning body w

Kangning Cui, Ruoning Li, Sam L. Polk, Yinyi Lin

Hyperspectral images (HSIs) provide exceptional spatial and spectral resolution of a scene, crucial for various remote sensing applications. However, the high dimensionality, presence of noise and outliers, and the need for precise labels of HSIs present significant challenges to HSIs analysis, motivating the development of performant HSI clustering algorith

Erik Frieling, Riley A. Stewart, James L. Booth, Kirk W. Madison

Atomic sensors have shown great promise for density and pressure metrology in the high, ultra-high, and extremely-high vacuum regimes. Specifically, the density of background gas particles in vacuum can be determined by measuring the collision rate between the particles and an ensemble of sensor atoms. This requires preparing the sensor atoms in a particular

Diane Y. H. Shi

In this paper, we establish a connection between Rogers-Ramanujan-Gordon type overpartitions to lattice paths with four kinds of unitary steps. By establishing the bijective relationship between overpartitions and lattice paths, we demonstrate that the theorems provided by Chen, Sang and Shi can be formulated in the form of lattice paths. Subsequently, inspi

Bibhas Manna, Arnob Saha, Zhouhang Jiang, Kai Ni

Reliability issues stemming from device level non-idealities of non-volatile emerging technologies like ferroelectric field-effect transistors (FeFET), especially at scaled dimensions, cause substantial degradation in the accuracy of In-Memory crossbar-based AI systems. In this work, we present a variation-aware design technique to characterize the device le

Lele Cong, Deshi Li, Kaitao Meng, Shuya Zhu

Vehicle localization is essential for intelligent transportation. However, achieving low-latency vehicle localization without sacrificing precision is challenging. In this paper, we propose a road-aware localization mechanism in heterogeneous networks (HetNet), where distinct features of HetNet signals are extracted for two-spatial-scale position mapping, en

Jiang Yan, Xing-Gang Wu, Zhi-Fei Wu, Jing-Hao Shan

In this paper, we present an improved analysis of the top-quark pair production via the process $e^{+}e^{-}\to \gamma^{*}\to t\bar{t}$ near the threshold region up to next-to-next-to-next-to-leading order (N$^3$LO) QCD corrections. Near the threshold region, the top-quark velocity $v$ tends to zero, leading to Coulomb singularity. To achieve a reasonable pre

Michael B. Law, Isaac M. Lopez, Daniel Santiago

We establish a weighted positive mass theorem which unifies and generalizes results of Baldauf--Ozuch and Chu--Zhu. Our result is in fact equivalent to the usual positive mass theorem, and can be regarded as a positive mass theorem for smooth metric measure spaces. We also study Dirac operators on certain warped product manifolds associated to smooth metric

Jarod Hattab, Eran Palti

The Emergence Proposal is the idea that all kinetic terms for fields in quantum gravity are emergent in the infrared from integrating out towers of states. It predicts that in a supersymmetric string theory context, the tree-level prepotential terms can be recovered precisely by integrating out a tower of non-perturbative states. In this note we present a ne

Lior Bary-Soroker, Arno Fehm, Sebastian Petersen

We study the preservation of the Hilbert property and of the weak Hilbert property under base change in field extensions. In particular we show that these properties are preserved if the extension is finitely generated or Galois with finitely generated Galois group, and we also obtain some negative results.

Yong-Kang Huang, Yao Ji, Yue-Long Shen, Chao Wang

We determine for the first time the renormalization-group (RG) evolution equation for the $B$-meson soft function dictating the non-perturbative strong interaction dynamics of the long-distance penguin contributions to the exclusive $b \to q \ell^{+} \ell^{-}$ and $b \to q \gamma$ decays. The distinctive feature of the ultraviolet renormalization of this fun

Vincenzo Caligiuri, Hyunah Kwon, Andrea Griesi, Yurii P. Ivanov

Nanoporous metals are a class of nanostructured materials finding extensive applications in multiple fields thanks to their unique properties attributed to their high surface area and interconnected nanoscale ligaments. They can be pre-pared following different strategies, but the deposition of an arbitrary pure porous metal is still challenging. Recently, a

Elnaz Amirkhanlou, Behnam Mohammadi

Recently, the LHCb collaboration has analyzed the decay of $B_s^0\rightarrow \chi_{c1}(3872)(\rightarrow J/\psi \pi^+ \pi^-) \pi^+ \pi^-$ and reported the ratio of the branching fractions to the $B_s^0\rightarrow \psi(2S)(\rightarrow J/\psi\pi^+\pi^-)\pi^+\pi^-$ decay. The results of this study have measured as a ratio of branching fractions as{\setlength\ar

Christian Simon, Sen He, Juan-Manuel Perez-Rua, Mengmeng Xu

Solving image-to-3D from a single view is an ill-posed problem, and current neural reconstruction methods addressing it through diffusion models still rely on scene-specific optimization, constraining their generalization capability. To overcome the limitations of existing approaches regarding generalization and consistency, we introduce a novel neural rende

Tie-Fu Zhang, Chengxi Li, Yitong Pei, Kai Liu

We investigated the impact of Non-Hermitian gravitational potentials on the spatial distribution of Bose-Einstein condensate (BEC) wave functions. Through numerical solutions of the Gross-Pitaevskii (GP) equation, we observed that the imaginary component of Non-Hermitian gravitational potentials affects the spatial periodicity of the BEC wave function phase,